|
|
Absolute deviation, 绝对离差4 s# G% U2 y8 I3 y% V, s
Absolute number, 绝对数
1 E) f6 h$ \6 l' y* ` XAbsolute residuals, 绝对残差
0 J4 _: q! C2 vAcceleration array, 加速度立体阵
- W% r) T$ i, \Acceleration in an arbitrary direction, 任意方向上的加速度
$ H' u. Q% f6 a& J* S. r; rAcceleration normal, 法向加速度
1 e) C! g2 L% q, }' iAcceleration space dimension, 加速度空间的维数# K, h! h, {2 ?: J$ j, m" o
Acceleration tangential, 切向加速度* s b* C$ g$ s k
Acceleration vector, 加速度向量# M9 }- y8 T) d3 W$ ?0 J6 s3 P! G2 |8 ~
Acceptable hypothesis, 可接受假设 Q. O' ?. G) V) E$ ^
Accumulation, 累积
6 k$ E- O5 w4 p' m5 F% jAccuracy, 准确度
" J1 p1 b4 G' U9 k* m$ k/ H4 jActual frequency, 实际频数
! r* L( t5 e9 }4 G6 WAdaptive estimator, 自适应估计量
% T0 k: a7 V% U6 R. K7 c" ]% EAddition, 相加
! ~7 u( K5 ^$ ]/ _7 o* hAddition theorem, 加法定理0 a& O! ~! j( |: j+ S W
Additivity, 可加性
1 v# _7 Y l( Q* x3 tAdjusted rate, 调整率
7 W! k& ^% O; y5 r" T3 `' nAdjusted value, 校正值0 s( E z% [% U
Admissible error, 容许误差
) D; t# @8 |, b/ L5 Y' ]Aggregation, 聚集性
0 q8 S; `" W1 V2 e# dAlternative hypothesis, 备择假设' I7 u/ Y/ G* V+ M0 O' c
Among groups, 组间
7 c7 [5 J9 G! j1 x4 g! ZAmounts, 总量
0 P, R0 g# }- `. M8 x1 ^: [- PAnalysis of correlation, 相关分析
% R$ j0 x A( d6 E# b4 SAnalysis of covariance, 协方差分析
5 w1 M Q$ T1 h2 E3 H) m: TAnalysis of regression, 回归分析5 L; c: d' V Z h( U' o' K
Analysis of time series, 时间序列分析& U" {9 {, L6 y! {8 r
Analysis of variance, 方差分析
1 b+ @0 l8 S1 U( b4 N, wAngular transformation, 角转换
& V1 P, t) N0 ^4 A6 b+ ~! @1 _ANOVA （analysis of variance）, 方差分析
. C/ d2 u1 P* a+ U, h- `2 TANOVA Models, 方差分析模型, i- [7 d! Q: \7 R/ j3 a4 Y
Arcing, 弧/弧旋
, }* i }. j* ?7 h# BArcsine transformation, 反正弦变换) `1 j. c& D J, p S0 b$ m& p
Area under the curve, 曲线面积
$ g) ]& t$ T8 c* r. ?AREG , 评估从一个时间点到下一个时间点回归相关时的误差 6 E) A# R* Q' v7 _( j8 j( L6 n
ARIMA, 季节和非季节性单变量模型的极大似然估计 8 [9 P+ i9 i+ H2 h, V9 S) r! y
Arithmetic grid paper, 算术格纸# t8 j, d# U G" n3 e+ D
Arithmetic mean, 算术平均数
" T. @ I$ s( v. tArrhenius relation, 艾恩尼斯关系+ @/ w/ F8 I, d
Assessing fit, 拟合的评估4 q- v T; i1 B% l+ e! N
Associative laws, 结合律7 c) q- \/ ~" S% o
Asymmetric distribution, 非对称分布
+ g/ ~6 X: `2 ]8 RAsymptotic bias, 渐近偏倚/ P( G: U8 ^2 C8 b
Asymptotic efficiency, 渐近效率
. U1 @4 v2 Z6 f5 ?$ W; _3 Q4 iAsymptotic variance, 渐近方差3 {# p: m% [6 ^
Attributable risk, 归因危险度
1 ]- s/ U+ m! ]& Q& m1 QAttribute data, 属性资料
* T1 B& _) g3 {/ c' GAttribution, 属性
4 W9 Q# G5 x: J" D6 _+ Z- oAutocorrelation, 自相关3 ^& k8 J+ |6 L$ _( k6 T: v
Autocorrelation of residuals, 残差的自相关) h7 V5 f* I8 n9 h6 g
Average, 平均数# U- }1 i, W2 | O4 O
Average confidence interval length, 平均置信区间长度/ N! c) H! V4 `! J: M2 N2 S- \
Average growth rate, 平均增长率
0 Z9 _( T4 r- c2 I0 G; [4 OBar chart, 条形图
, {8 b0 B/ }7 A3 {6 x8 QBar graph, 条形图
9 i: [0 J! @! z' W0 Z, F6 hBase period, 基期/ h' Y- J; `- }3 h! A4 V
Bayes' theorem , Bayes定理
- p g( Y0 r$ G' B& gBell-shaped curve, 钟形曲线
8 W+ Q3 z" a7 X) s- y9 g5 WBernoulli distribution, 伯努力分布6 D# b4 k% @6 E F+ {( V3 N+ z' H
Best-trim estimator, 最好切尾估计量; H4 N8 M% }4 I9 u$ Z
Bias, 偏性
# M0 }& @0 ]- X, IBinary logistic regression, 二元逻辑斯蒂回归
/ J- |6 [0 h& U5 \- x, Y& Z, A+ \Binomial distribution, 二项分布
5 T8 x7 I0 P% SBisquare, 双平方
$ \9 b4 H: E! J, T6 xBivariate Correlate, 二变量相关
: w; q" a$ D6 u0 JBivariate normal distribution, 双变量正态分布" e; D! K' `" n8 T+ _" [
Bivariate normal population, 双变量正态总体
( N' p$ \- P: m; ?8 wBiweight interval, 双权区间
4 t6 ?7 J; d3 V* R; [0 R! H) \& mBiweight M-estimator, 双权M估计量& _% I3 n- d) ?+ x! |7 d
Block, 区组/配伍组
6 [( {& J" X) u5 A/ N3 lBMDP(Biomedical computer programs), BMDP统计软件包
% ^6 L9 J4 z, ^6 `Boxplots, 箱线图/箱尾图9 }2 i9 |) k; F" o0 a3 H+ m' {
Breakdown bound, 崩溃界/崩溃点) z( D1 k, ^5 U" l' M6 y; y. g$ U1 S# T
Canonical correlation, 典型相关
& k+ W1 v t& j2 C" ^Caption, 纵标目
5 w; \% g$ G9 j, _" aCase-control study, 病例对照研究
3 m( D$ K& `5 U7 X6 j$ P: c) NCategorical variable, 分类变量
& @5 n' y0 i3 W% j( D, dCatenary, 悬链线
; ]& n/ s' X& k+ y4 zCauchy distribution, 柯西分布
9 C2 a9 N. O( `4 o: J( hCause-and-effect relationship, 因果关系
5 E( C6 t2 C, ?Cell, 单元
c% R- d2 y. G6 u4 bCensoring, 终检. s9 i0 g7 `, U# b" ]
Center of symmetry, 对称中心
* P) S: j$ [# A+ x8 `Centering and scaling, 中心化和定标! x: o: N/ h4 b, ]/ }. E6 U2 v; M
Central tendency, 集中趋势
# A2 a0 V, r! x. p- L4 H6 kCentral value, 中心值
, {, c' u2 |9 o7 [0 L6 K3 cCHAID -χ2 Automatic Interaction Detector, 卡方自动交互检测
$ _" y# M4 O; R: Z9 B5 lChance, 机遇* ]9 u0 R- f4 `# g ]9 g5 }' H; d
Chance error, 随机误差! a" o) E v$ E6 g4 |* G& C
Chance variable, 随机变量
5 }9 o% L" i/ }6 b; ^Characteristic equation, 特征方程1 V5 ~& ]: {9 ^9 l+ O* e! t4 A* J
Characteristic root, 特征根
6 U/ {& ^2 b9 T( j, u. pCharacteristic vector, 特征向量0 D- U: I% V8 |( Q8 ~, `3 I' B
Chebshev criterion of fit, 拟合的切比雪夫准则
8 p3 t' k- ^. t Q. _Chernoff faces, 切尔诺夫脸谱图
5 v- K9 v$ N3 m( BChi-square test, 卡方检验/χ2检验
# d. z% `/ M j, x1 j C* m, HCholeskey decomposition, 乔洛斯基分解
% r3 o/ e6 p1 Z; P& M/ nCircle chart, 圆图
6 A4 v3 L0 ^0 t1 TClass interval, 组距8 A5 @; ~" |7 D0 `# a
Class mid-value, 组中值7 z) d4 g5 V! }0 }, M) S
Class upper limit, 组上限4 r/ S/ R2 q3 D
Classified variable, 分类变量
" y8 x' h/ \5 V( F% R, LCluster analysis, 聚类分析9 C) M: k& d8 v! g
Cluster sampling, 整群抽样% W2 R& I! ]" O5 ?3 J0 H
Code, 代码+ X: L* [% q, A# d7 ] d
Coded data, 编码数据+ T% H1 I! J3 {" K, ^* u
Coding, 编码# V; Q7 l W* _! V% \
Coefficient of contingency, 列联系数- h# L7 C7 u: F3 n1 _" Y9 ]
Coefficient of determination, 决定系数
9 ^6 A7 K% V4 n8 z" F& }$ nCoefficient of multiple correlation, 多重相关系数2 J" d% M; L( p9 v
Coefficient of partial correlation, 偏相关系数
! }8 w/ g/ Z" X9 | f' a1 ^4 a8 C2 ICoefficient of production-moment correlation, 积差相关系数, x% S/ N' e. P2 O/ {
Coefficient of rank correlation, 等级相关系数
/ m8 b1 }4 ~! YCoefficient of regression, 回归系数
4 C9 }% ^; ^2 X" c5 C3 uCoefficient of skewness, 偏度系数2 H& s- f6 O, }9 j3 z- R
Coefficient of variation, 变异系数
' F3 @: i* {& B3 R! p }- t; S+ xCohort study, 队列研究* R$ R7 N) ]9 V. D
Column, 列
8 \0 x4 D$ _. Q: U0 k- @+ K0 ?8 J0 WColumn effect, 列效应) F* H7 V1 j* K. P4 G1 a
Column factor, 列因素
- s9 J3 [2 N# e+ B5 pCombination pool, 合并% B* E7 p! C2 v
Combinative table, 组合表
% R: @( [. Y1 ?) R0 G$ mCommon factor, 共性因子: I1 H# [+ q; T
Common regression coefficient, 公共回归系数* \; _7 R. N# k5 @5 J
Common value, 共同值% [8 F" g# g4 ?" k9 L9 R3 z) J
Common variance, 公共方差
, F$ I, q ~3 p0 I# qCommon variation, 公共变异
8 i$ t, C# Z2 u) t" e4 ] F0 Q4 BCommunality variance, 共性方差
- |: j* j- w2 \, h; h3 FComparability, 可比性- {- t2 o. a2 c3 [
Comparison of bathes, 批比较/ Q& F% a9 v, _" J, y
Comparison value, 比较值
- N! Q$ o3 f6 F$ E+ V* TCompartment model, 分部模型8 h: O1 X' j( d" n% ^, X9 J" X! B
Compassion, 伸缩
$ _7 C: y3 x9 D! [% ~+ j7 {Complement of an event, 补事件4 T8 ^' O4 c: J, Z$ T
Complete association, 完全正相关
1 S1 E4 b: X) ^: WComplete dissociation, 完全不相关
! K7 v4 e; ~, s; A; nComplete statistics, 完备统计量
) A. m# W' p# s* g8 a8 Z: `% sCompletely randomized design, 完全随机化设计: g- E& ^4 J0 H( U3 _$ ?7 D
Composite event, 联合事件6 u h9 \% w: G5 l: |
Composite events, 复合事件
7 o9 A, M4 A ?0 DConcavity, 凹性9 W' ^2 D3 `) M, j8 r$ q
Conditional expectation, 条件期望& V! k+ N$ O/ F O, B; L5 Z; E
Conditional likelihood, 条件似然
$ R$ B% L4 O, |Conditional probability, 条件概率1 ~. c( v* o( t9 y
Conditionally linear, 依条件线性& @* \) B. Q! `; Y
Confidence interval, 置信区间# ^; y+ N; ^2 c' k% L9 k" {, g
Confidence limit, 置信限' M+ R1 w! r2 W7 Z. q1 @) c4 ^4 c
Confidence lower limit, 置信下限
( a! O$ [3 G" }2 J8 XConfidence upper limit, 置信上限
9 W, r& L5 l7 sConfirmatory Factor Analysis , 验证性因子分析 _5 \6 j1 A( G7 B! J
Confirmatory research, 证实性实验研究
" {6 x5 t4 h) W) a/ T7 S- ~" xConfounding factor, 混杂因素6 p% }5 L0 d& O& o& y, n
Conjoint, 联合分析
) ?6 F: z# J) i) JConsistency, 相合性
% M9 h+ l/ r5 t; gConsistency check, 一致性检验
5 Q( W! o' n4 P. g4 c' B5 M k1 pConsistent asymptotically normal estimate, 相合渐近正态估计
! u" R& e2 \+ X8 Q" ZConsistent estimate, 相合估计
' o3 s$ ]4 A! C( d: y' S6 S3 _' ?Constrained nonlinear regression, 受约束非线性回归
3 c/ w K; |7 a) L- s1 IConstraint, 约束7 G$ \' b: x, _
Contaminated distribution, 污染分布
$ V% k/ e3 \ o3 UContaminated Gausssian, 污染高斯分布
+ h' [3 m: ?9 S1 yContaminated normal distribution, 污染正态分布
0 B. F$ x2 c' q$ N$ R( xContamination, 污染
7 P5 B; M! |" M( } d. S' \Contamination model, 污染模型) o6 Q8 s: t3 y! k/ d% E
Contingency table, 列联表1 G, ^% j. K4 K# M7 `; V z
Contour, 边界线
2 C" B5 S; D- h6 F' ]; S- @' @Contribution rate, 贡献率
l3 ^6 r5 n0 b; d2 k/ E) B1 FControl, 对照
/ v# \" R9 ?. J0 P8 {$ sControlled experiments, 对照实验: F' u4 P1 T6 ^% K& P) L
Conventional depth, 常规深度
- A4 {4 d% ^0 Q% J* oConvolution, 卷积
2 C4 n* j8 v5 }Corrected factor, 校正因子1 |* ^, V- L+ u `) @0 g, Y
Corrected mean, 校正均值, [5 J+ S' Q h- Z; {+ G4 l
Correction coefficient, 校正系数8 L+ B; y3 l% X4 |
Correctness, 正确性
/ j$ P4 T, z) L3 z K) hCorrelation coefficient, 相关系数
' B$ y5 a) h( Z# q% F) l) Z4 ]Correlation index, 相关指数8 ^8 U1 M9 V/ w' m3 V t! Q& {
Correspondence, 对应
( S9 }: w5 N5 h2 O9 cCounting, 计数1 c, L- s; \2 o# O; U
Counts, 计数/频数4 N$ L) u; n y+ m: |
Covariance, 协方差! e# K! l; w& J% w+ V E
Covariant, 共变 7 K; {! D" s. O1 C4 x
Cox Regression, Cox回归
" A9 j' z2 a" _2 WCriteria for fitting, 拟合准则9 x5 F8 _' r) X: q
Criteria of least squares, 最小二乘准则
6 x* ]& Q9 C9 x& q$ r; UCritical ratio, 临界比! C+ l) A, z! d: }: w
Critical region, 拒绝域
* M' k7 z" q a& QCritical value, 临界值# R. h @9 c4 N K
Cross-over design, 交叉设计
* c9 L9 t, h! Q% QCross-section analysis, 横断面分析 d% Y( N. U' V5 I1 K* l2 E$ K' ]
Cross-section survey, 横断面调查
' {$ M- Q) g; K* z; K; g5 }Crosstabs , 交叉表 " W. O) B( P5 E# o4 F1 n% i _; ]+ _
Cross-tabulation table, 复合表1 \& ^9 v9 B$ m' @
Cube root, 立方根8 Y7 @6 ?$ `& z" ]. p5 r9 k$ k
Cumulative distribution function, 分布函数. s7 ~/ |: d1 e
Cumulative probability, 累计概率 o4 D/ ?4 y8 u* u/ c' U% C
Curvature, 曲率/弯曲
& N. W( Y2 a; @% e+ [4 [: F7 j! }Curvature, 曲率0 M# k# p% n4 U& c h+ j, U+ P9 f
Curve fit , 曲线拟和
$ n6 G- q7 i; _& @ s' s3 |Curve fitting, 曲线拟合/ `$ R9 v6 D% Z) r( M# [* U5 s
Curvilinear regression, 曲线回归! w) W$ [$ z7 G/ ^$ l q' b
Curvilinear relation, 曲线关系7 i: r/ T8 }6 l5 f
Cut-and-try method, 尝试法
. ~0 `) x. k2 F" h! N) L) R' UCycle, 周期7 l( J/ ~, x- M8 ^ Q: D+ ~9 z/ V& h
Cyclist, 周期性
) i6 A: A; F, H, ?D test, D检验( ?& R7 p, U2 k3 n
Data acquisition, 资料收集+ Y I/ f0 q2 J- R+ t [& Z+ f
Data bank, 数据库
& W& n# y* ]/ ~/ I J! BData capacity, 数据容量" Y$ ~6 b- ~+ ?1 K _1 M5 M# W
Data deficiencies, 数据缺乏
- f" o! W. A# M9 V9 D+ f3 rData handling, 数据处理 d7 J' }% Z! y! |
Data manipulation, 数据处理3 O. P+ J, i5 ?3 n3 {, x
Data processing, 数据处理
9 `) J" i# q' R! m; XData reduction, 数据缩减6 K; ~3 k( W; r; t' Y; u/ X
Data set, 数据集' O; I* W& D' W0 @) z
Data sources, 数据来源
. D% t# K. f( uData transformation, 数据变换" P2 q! s' ~; @- x' _: f
Data validity, 数据有效性
4 G* }- e" N6 y4 |Data-in, 数据输入4 R3 U4 w' ?; _) T9 Y
Data-out, 数据输出3 E8 D4 q! n+ r( {8 G
Dead time, 停滞期! e) Z2 X: S+ g
Degree of freedom, 自由度
: U- {& Z1 C% U5 MDegree of precision, 精密度
: O1 B8 s; d: Y: `2 |- vDegree of reliability, 可靠性程度( Y- g; K7 x6 L0 D: s
Degression, 递减
9 d' w5 p0 o/ I5 xDensity function, 密度函数) Z! c4 ?: g7 G2 b
Density of data points, 数据点的密度
. U+ r1 S" s# j% x6 eDependent variable, 应变量/依变量/因变量
+ G+ Y K: i2 A+ l: t( q6 ADependent variable, 因变量
" k9 a0 q0 q: b! l8 aDepth, 深度) E2 i0 N- h% n5 b3 e7 R: O, \
Derivative matrix, 导数矩阵+ c0 {0 V, d$ F6 N
Derivative-free methods, 无导数方法8 ^7 Q* ]% {2 W2 f
Design, 设计
! U# D, b0 I2 c: fDeterminacy, 确定性
7 q9 @5 Y2 L) ^; F+ z" sDeterminant, 行列式
* r6 Y& J5 @3 U2 F4 I7 fDeterminant, 决定因素6 H: y3 I: A4 R; z8 H
Deviation, 离差/ O7 A: J) o4 j
Deviation from average, 离均差
4 L) |$ q# p. N3 H! aDiagnostic plot, 诊断图
* r" O5 a2 T/ S, r x# j8 SDichotomous variable, 二分变量2 [* ^5 i7 g& i, [, w
Differential equation, 微分方程
( x! j! K7 {9 k6 Y8 ODirect standardization, 直接标准化法; l! `1 K: d$ |* U2 {9 B
Discrete variable, 离散型变量
" [0 W& Y j2 v+ MDISCRIMINANT, 判断 2 f' g) Y. \3 v5 F7 I
Discriminant analysis, 判别分析
& y8 x# K1 `& T0 x* z2 Y$ e! J aDiscriminant coefficient, 判别系数
: m( j* Q# a/ J! ]Discriminant function, 判别值
% I4 ^ [$ W# P% sDispersion, 散布/分散度5 Q' Y) O% s n8 W. j6 X% i
Disproportional, 不成比例的
$ O. ?- G6 I2 z. e# GDisproportionate sub-class numbers, 不成比例次级组含量3 H/ y! B/ ]8 \/ n5 @5 y
Distribution free, 分布无关性/免分布2 X* ~: o6 E; S3 C7 U
Distribution shape, 分布形状
/ S2 l5 B+ n! E3 M: gDistribution-free method, 任意分布法% e2 \* U/ | B# I
Distributive laws, 分配律& K' a+ E& e$ w: F* g
Disturbance, 随机扰动项
, x& a* d k9 I" A$ QDose response curve, 剂量反应曲线
6 f& t& \+ B; rDouble blind method, 双盲法
; m0 J: B8 s% p, i) V; ^7 S' wDouble blind trial, 双盲试验
1 n; C+ J' r3 O. i' XDouble exponential distribution, 双指数分布6 b1 t+ T# |. R' w, C
Double logarithmic, 双对数
# u6 P8 }0 b5 c5 B6 M% K* z4 {% eDownward rank, 降秩. ]6 L& ^$ o1 d! _
Dual-space plot, 对偶空间图
) P+ Z+ k5 Z( P4 PDUD, 无导数方法5 {% R; O) ]5 D+ M6 J9 @
Duncan's new multiple range method, 新复极差法/Duncan新法
+ ?3 i" O* P- O1 ^7 y# R5 `& ZEffect, 实验效应
) ~, y& O8 b' V, g3 |$ @Eigenvalue, 特征值 R" P8 a4 r! m5 B6 j8 s
Eigenvector, 特征向量5 x" t5 g% e5 Z, d' ~: V" o
Ellipse, 椭圆
9 D7 ^/ b$ o8 I' w7 q" bEmpirical distribution, 经验分布
" ~! w% _1 i( C# I6 g- |' JEmpirical probability, 经验概率单位6 ^/ S& w& e2 P( Y. I2 K$ T
Enumeration data, 计数资料+ c9 S: Q6 a5 U9 e: h. W! F4 n- E3 K9 p
Equal sun-class number, 相等次级组含量
7 k d( U6 H. X, q9 G4 YEqually likely, 等可能. p: |% I" v8 M% B) U) Z
Equivariance, 同变性
8 z/ v! a: A0 } t, wError, 误差/错误
5 ^/ X, {& \; y* H; _' uError of estimate, 估计误差
$ ~- G" u* j$ `, \Error type I, 第一类错误 I+ q% I+ w3 \( ]! g: X8 {
Error type II, 第二类错误4 Z; m/ P: D. [- d
Estimand, 被估量1 o5 O0 y4 s) T
Estimated error mean squares, 估计误差均方
+ F6 I! w/ _# x a$ l- eEstimated error sum of squares, 估计误差平方和
, G) i4 @" m: MEuclidean distance, 欧式距离' P0 }, ?! A9 o! A
Event, 事件7 {: t5 W1 ~( Q6 Z2 G# D
Event, 事件) H0 S1 ]; K) w3 p% d2 x7 H
Exceptional data point, 异常数据点% |* u. _, P, \8 e7 X
Expectation plane, 期望平面7 k0 `, d0 S" @, }1 B" v! ^; m
Expectation surface, 期望曲面* T; s% g9 w; {, ^" ?
Expected values, 期望值6 m' N" n& [# k, O( `! T' Z
Experiment, 实验9 U3 [9 G. {4 k4 a. K X9 p
Experimental sampling, 试验抽样
0 g! Q+ q3 `) g$ P; ^7 @Experimental unit, 试验单位, |+ [6 O- B. o& P
Explanatory variable, 说明变量1 d N6 S! y. [
Exploratory data analysis, 探索性数据分析% ? ?2 K/ z. I$ a0 X; n/ V/ `
Explore Summarize, 探索-摘要2 e1 U8 u( s6 o% B
Exponential curve, 指数曲线% J( U9 b0 t. |; A8 m7 `: p- f
Exponential growth, 指数式增长8 ?# p; A/ m+ I% V5 E1 A
EXSMOOTH, 指数平滑方法
; @( [4 Z$ m- O6 e7 g VExtended fit, 扩充拟合/ [2 `/ X5 M; \% o' W) [" ]
Extra parameter, 附加参数
- e( `5 y( r7 o/ zExtrapolation, 外推法
" ^# @( P4 D' c- {7 u5 K- \/ _Extreme observation, 末端观测值- L* M4 d1 U& e- a# v# Q
Extremes, 极端值/极值
4 T, l3 b6 q0 c9 L: x, CF distribution, F分布; b. v) G- Q2 ?" c; v: S2 p9 b
F test, F检验6 |( i! L0 e: i
Factor, 因素/因子4 S1 c F% v2 O1 \) q) S
Factor analysis, 因子分析 Y3 ^% \- T2 Z: j e& r6 |- ]6 b5 `
Factor Analysis, 因子分析6 G' n# @* D( k% U
Factor score, 因子得分
, T) \; q) Q9 y0 EFactorial, 阶乘' u% m% ?( Y1 n/ L% f
Factorial design, 析因试验设计. t( b2 I- ?# \' P
False negative, 假阴性
7 i N. I' M3 HFalse negative error, 假阴性错误: x( l, g& I) g% L5 C: [+ x, X
Family of distributions, 分布族
% `* f1 T( K2 OFamily of estimators, 估计量族
6 g( Q0 A2 `' |/ t# M1 LFanning, 扇面
. d2 N7 r f: Q5 l/ M1 w! C* B, ^Fatality rate, 病死率. K) X; B+ }0 d1 q8 d, W9 t! T
Field investigation, 现场调查& {- K) }; a& z C" k* X
Field survey, 现场调查+ X# [* E5 R) l! E/ X+ p
Finite population, 有限总体
3 l, c0 k- d8 {5 p7 @( TFinite-sample, 有限样本0 t+ n* p5 _" J0 _# u1 F
First derivative, 一阶导数
( ?' m( N2 \. {7 B. R7 J6 iFirst principal component, 第一主成分
+ w8 h0 v# L. q0 z5 X4 NFirst quartile, 第一四分位数: e" _0 b7 [! G: {, ]
Fisher information, 费雪信息量
4 }+ S, @; Y. }/ ?' G e3 i. qFitted value, 拟合值
% o: Y( d8 g" `* b7 DFitting a curve, 曲线拟合8 | W$ F6 C! u. o: o. `' c% z
Fixed base, 定基
0 ?5 o7 m! R5 b0 [Fluctuation, 随机起伏$ Y! X+ I. l0 Y$ N: e' \
Forecast, 预测
$ c C: {- _$ _Four fold table, 四格表
+ V F4 d$ ?5 c7 Z2 [& QFourth, 四分点
1 Q; `! G I' ?. j" r3 u3 M. A8 @Fraction blow, 左侧比率, e: u- G) D8 |1 ?
Fractional error, 相对误差
2 Z* e/ F- y5 _! d1 \' [Frequency, 频率
7 R3 K! p2 f; m& u$ kFrequency polygon, 频数多边图
' a5 [! V# i' _' d% EFrontier point, 界限点; q1 T# O% s( l4 |$ V' B! E* m' p
Function relationship, 泛函关系0 V3 j7 \5 c% N4 R3 F+ p
Gamma distribution, 伽玛分布, d O# Z9 K8 t o- B+ e
Gauss increment, 高斯增量1 ]- t# ~* S# G. r/ l R, R5 B
Gaussian distribution, 高斯分布/正态分布
8 W( |7 F' l& Y7 BGauss-Newton increment, 高斯-牛顿增量
# L% g0 }" ^, ^- x& H% }, uGeneral census, 全面普查
, [3 W1 p2 m! J( F2 `3 G/ b; a6 yGENLOG (Generalized liner models), 广义线性模型
: V7 P/ I7 u# b+ v a$ UGeometric mean, 几何平均数
! N7 G2 |3 A8 zGini's mean difference, 基尼均差4 ~/ J' e$ q+ T& [2 y, ]
GLM (General liner models), 一般线性模型
% s8 q t( h9 A, }Goodness of fit, 拟和优度/配合度2 K+ a6 g" U5 G
Gradient of determinant, 行列式的梯度9 f( ^2 L7 h( R; @9 E
Graeco-Latin square, 希腊拉丁方9 V+ x" q5 Q2 ], s* O7 w
Grand mean, 总均值
% B) Q9 `* a6 X) g: s0 v3 TGross errors, 重大错误" }7 ?4 ]$ ?# [1 k) V w
Gross-error sensitivity, 大错敏感度
; w) D+ T: S P) iGroup averages, 分组平均* Y5 X% B3 W7 v5 ^4 V& Y6 ~8 R6 R
Grouped data, 分组资料
" e3 m$ X, l' o+ g. J+ DGuessed mean, 假定平均数: s4 ?) l5 n; W
Half-life, 半衰期
6 S. K" ?9 u1 v- w* H$ p9 BHampel M-estimators, 汉佩尔M估计量
7 h/ a2 U5 D$ Q8 ?0 h+ U3 iHappenstance, 偶然事件8 \2 K1 v% ]5 M0 X. T2 T" [8 a
Harmonic mean, 调和均数
5 D( u' \) [% F" B {2 h7 R3 P8 YHazard function, 风险均数9 G7 S8 n5 O9 z/ h
Hazard rate, 风险率! F2 Q$ B6 f" ~9 l! R" o& R
Heading, 标目
# Z+ e3 O! C1 B# ]8 oHeavy-tailed distribution, 重尾分布
* [9 J4 w! q _8 T: s) ~Hessian array, 海森立体阵0 `8 R/ |) M, R1 n! _
Heterogeneity, 不同质
6 j e( G) w, xHeterogeneity of variance, 方差不齐
% o: J" K; F. G* U" aHierarchical classification, 组内分组2 y# S; G ]- b) u* `
Hierarchical clustering method, 系统聚类法
" @, b+ K+ |5 OHigh-leverage point, 高杠杆率点& g# M' [. C5 k- G
HILOGLINEAR, 多维列联表的层次对数线性模型
( \3 p" U& z* X, c' k( B eHinge, 折叶点) J, t+ p4 l% K
Histogram, 直方图
: o; {( d+ f9 z& J, n4 RHistorical cohort study, 历史性队列研究 + s6 [: C2 F9 s! N+ ]
Holes, 空洞
, e) h9 w0 H+ Y& t6 lHOMALS, 多重响应分析3 s" b) l W( ^+ B
Homogeneity of variance, 方差齐性
" ^1 S4 L$ d& N4 ~5 pHomogeneity test, 齐性检验
3 u2 U1 c$ j% B( W2 `, @! k6 ?& h! kHuber M-estimators, 休伯M估计量3 \' {: f6 ?; i9 [; q
Hyperbola, 双曲线& a7 o" t2 S9 t$ H5 B
Hypothesis testing, 假设检验5 s! L: x, @" }8 ^8 `
Hypothetical universe, 假设总体
$ `. {9 V8 U/ X3 g T D& ]Impossible event, 不可能事件3 D4 h, l8 l, a6 M, `- l; g
Independence, 独立性) i7 b, W# Z" Y9 f
Independent variable, 自变量; p' p% Y/ R% K; Z( j+ ~
Index, 指标/指数
" F( |0 t. y& o# GIndirect standardization, 间接标准化法
& }( p* Z. f: e% lIndividual, 个体# A7 F) O0 p( i) p5 v! }# a: P
Inference band, 推断带/ R G" t! k5 i$ V: `
Infinite population, 无限总体0 g3 m: n1 `! }2 j1 B3 @9 X
Infinitely great, 无穷大: f K' e/ r- |+ T$ C
Infinitely small, 无穷小
+ v& S- G' O- U' {Influence curve, 影响曲线
, j/ f7 D- j1 r3 [, MInformation capacity, 信息容量+ S; G$ {. m' o! M. u
Initial condition, 初始条件% ~* Z0 }8 ?2 |$ P% K
Initial estimate, 初始估计值. t; [6 s5 ]& @: |2 J
Initial level, 最初水平
' S. P# ~1 l. }/ {5 \- K f$ rInteraction, 交互作用
( L+ t* D1 A; _$ n$ ~Interaction terms, 交互作用项
9 X# I# s, d2 PIntercept, 截距& c+ w9 q5 z7 E7 n3 l( b7 n
Interpolation, 内插法8 P% B) c; i/ L: I5 b5 o8 [
Interquartile range, 四分位距
3 e" u) u; K! `, l. [Interval estimation, 区间估计7 G& j$ Q( u. I1 i
Intervals of equal probability, 等概率区间
7 d/ C7 c$ L4 d# AIntrinsic curvature, 固有曲率
* o. s. u) k' x' x/ KInvariance, 不变性
) Q$ a5 c) C$ P4 i* YInverse matrix, 逆矩阵
/ C9 ?' H8 J2 Z5 MInverse probability, 逆概率4 J- R/ @7 b5 B1 s8 U3 }
Inverse sine transformation, 反正弦变换
& h5 {/ s9 y/ R' q, G# c% O ]. RIteration, 迭代 1 W; c2 Q) Z- ]+ Q* v9 S
Jacobian determinant, 雅可比行列式& s5 H; Q, S+ q7 H
Joint distribution function, 分布函数9 p! a" V7 l) X6 t
Joint probability, 联合概率( i4 ^# V7 |; z
Joint probability distribution, 联合概率分布* j/ L! B$ k4 T: g# d
K means method, 逐步聚类法
! J3 A: N) J3 m; S: s) SKaplan-Meier, 评估事件的时间长度
H- c& r. d+ i) B; {Kaplan-Merier chart, Kaplan-Merier图
( o' w- U8 m* e, mKendall's rank correlation, Kendall等级相关
' e+ _* T8 G! Y% }0 }4 J; I. ]9 OKinetic, 动力学
- E: [& y3 B& I. G' GKolmogorov-Smirnove test, 柯尔莫哥洛夫-斯米尔诺夫检验
9 d, b/ R" ]! y* _2 k. ~# yKruskal and Wallis test, Kruskal及Wallis检验/多样本的秩和检验/H检验
U3 K) Z9 Z2 k6 GKurtosis, 峰度' {6 O3 h8 X& s9 K: v
Lack of fit, 失拟' ^: i" p' k7 I1 I3 a M# l
Ladder of powers, 幂阶梯
8 O9 e" F) J: JLag, 滞后! _! P% U' U% m% V+ \
Large sample, 大样本
; f8 m& Z5 `1 h. ~& u/ h& I2 dLarge sample test, 大样本检验# X1 }7 |. x# {6 j
Latin square, 拉丁方
4 }0 }& T6 q2 N* O# }Latin square design, 拉丁方设计; N+ Z2 _4 {" {+ d8 {% `
Leakage, 泄漏
& h( f; R* A: J1 Y, ]" D( ^( d2 iLeast favorable configuration, 最不利构形; `3 Z" l# ]' ?
Least favorable distribution, 最不利分布
7 v' y9 q, E) g4 ^Least significant difference, 最小显著差法9 U$ c j6 R6 b8 _" t
Least square method, 最小二乘法
8 \# W4 k* A: ELeast-absolute-residuals estimates, 最小绝对残差估计4 m7 Y& \& M/ ?: A* f# l
Least-absolute-residuals fit, 最小绝对残差拟合' T& b' f/ M" T5 z; d, E1 F. \
Least-absolute-residuals line, 最小绝对残差线9 @/ y4 c7 N0 x9 Z5 C
Legend, 图例. x& H' W; D6 B
L-estimator, L估计量
, J8 s- O. m6 F3 ]$ _0 L& QL-estimator of location, 位置L估计量" o3 G; ^' D# o" U5 ^4 H
L-estimator of scale, 尺度L估计量- q# T6 _/ T2 H' _0 N) E( W( B: A
Level, 水平
, j+ r2 W8 _, _$ h WLife expectance, 预期期望寿命
4 c3 C' Q9 n+ R' d1 \" p8 `& @5 yLife table, 寿命表
1 {7 w, e3 G5 VLife table method, 生命表法
- x) n; Q- M4 G. ]Light-tailed distribution, 轻尾分布
- E) j; z8 o9 k! [Likelihood function, 似然函数( G6 C2 B! T/ |- ^) l
Likelihood ratio, 似然比
- @. J* c& Y; z& hline graph, 线图* `; r( o! h4 D& U( Y9 `+ _4 |
Linear correlation, 直线相关
, j L( G0 g* l, s& _1 { m9 \Linear equation, 线性方程
0 g$ r4 G* j% N! n, k$ JLinear programming, 线性规划6 r4 [8 ?! ]% V8 n+ Z% H
Linear regression, 直线回归
0 K6 n+ o# A1 g4 V" M, k: i/ FLinear Regression, 线性回归
+ K3 u, S7 M" P/ |* NLinear trend, 线性趋势. i# j3 j# V. D2 Z9 ?) U/ v" H- q
Loading, 载荷
6 g" {/ q8 Z5 ]& v; |. L% K# _) ZLocation and scale equivariance, 位置尺度同变性$ O" R8 N" `; I' N7 c
Location equivariance, 位置同变性
9 ]' e9 s7 g4 K+ M9 |. SLocation invariance, 位置不变性
# V7 t' q& W |; B# G2 ^) L" MLocation scale family, 位置尺度族6 z8 I$ |0 ]$ y
Log rank test, 时序检验 # w9 j/ D2 [& N+ ?
Logarithmic curve, 对数曲线. E0 @( y$ ]! c% ^
Logarithmic normal distribution, 对数正态分布; d8 O! J5 E+ B4 m, S0 Z+ d" g: j
Logarithmic scale, 对数尺度# Y: n1 B0 q0 j8 U; f. @2 U; O$ o
Logarithmic transformation, 对数变换
0 J! s$ r4 q# v$ {/ g1 \Logic check, 逻辑检查0 z x! m, v9 @1 z+ n
Logistic distribution, 逻辑斯特分布3 M' e3 Z6 t' Y3 J
Logit transformation, Logit转换4 i& Y6 W) J8 \0 H* T/ {5 [; u7 J/ b
LOGLINEAR, 多维列联表通用模型
9 M4 [3 A; H A8 J0 @/ J3 cLognormal distribution, 对数正态分布
4 t3 G7 [8 b6 ]9 Y' l7 `6 j9 sLost function, 损失函数
: Y- w3 Q% j! k* s3 J6 Z1 mLow correlation, 低度相关
' R, ]; F; q+ U" KLower limit, 下限2 S/ U2 h5 g& ~" W: e& R, C% R
Lowest-attained variance, 最小可达方差' @' d+ T4 E$ _. c% \. J8 x* ], ]
LSD, 最小显著差法的简称
* r- @0 B! X$ C3 J: D/ [Lurking variable, 潜在变量
3 ]- J$ K8 P: p) b$ \Main effect, 主效应. c) x3 d; S+ z1 ~/ Z' e. w& I
Major heading, 主辞标目
& }! [6 k; ~/ b0 p2 A' kMarginal density function, 边缘密度函数$ |4 O5 v7 r7 A4 G# A5 e& g$ V( L& Z
Marginal probability, 边缘概率
) w2 `' C- D! F2 V0 u3 sMarginal probability distribution, 边缘概率分布- K9 e* e0 q2 H# B* T6 t' ]* b- k
Matched data, 配对资料, a+ t; R K5 a
Matched distribution, 匹配过分布
/ V5 u/ p" K+ A" l1 X0 j6 V zMatching of distribution, 分布的匹配8 e! m" G! c7 O& t% V4 z2 G) s
Matching of transformation, 变换的匹配% I' F1 s+ r) s7 M( d/ _" F
Mathematical expectation, 数学期望* V/ F( g) f) q" _
Mathematical model, 数学模型
2 K- f) x; {5 I4 DMaximum L-estimator, 极大极小L 估计量
& \* i j1 S& o4 C' ?- Q0 MMaximum likelihood method, 最大似然法( }2 f: b/ g& {. P# T. S. r
Mean, 均数
" o1 G4 O" @& J/ ^: ]7 B( W3 V9 z( k# S" BMean squares between groups, 组间均方
1 e: ~6 d0 H. F9 f8 j* q8 X3 N# XMean squares within group, 组内均方
2 Q9 a2 S, S2 X+ v# E4 d4 A) N2 o% _6 MMeans (Compare means), 均值-均值比较
' A; {5 y- M) [1 Y' a# kMedian, 中位数0 c5 v# ^2 g+ X
Median effective dose, 半数效量. ~& r" f% |4 m8 Y" P
Median lethal dose, 半数致死量5 L5 c, r6 U. r6 ]1 z+ y0 m# C1 _
Median polish, 中位数平滑' {% N" H) p# z/ [. Q$ V
Median test, 中位数检验
% I4 K0 e$ b8 Z7 ^3 s1 PMinimal sufficient statistic, 最小充分统计量
" t( K4 I* A) y5 Y+ b9 FMinimum distance estimation, 最小距离估计
/ c+ g8 O& Y$ X1 t* _# ?8 wMinimum effective dose, 最小有效量9 h6 t* m1 T; U1 h( B6 M4 |
Minimum lethal dose, 最小致死量" H3 t7 D. |% Q2 f7 o3 h
Minimum variance estimator, 最小方差估计量
2 m1 P& h* P" y2 u# _0 Y9 JMINITAB, 统计软件包
+ F u' }( `5 K$ d* y; AMinor heading, 宾词标目- @- `* W/ Q0 I' G
Missing data, 缺失值
6 ^ X G( O7 w) t+ f$ ~Model specification, 模型的确定* Q. T/ o* E2 h
Modeling Statistics , 模型统计" G/ g7 {( P1 E! `
Models for outliers, 离群值模型
0 s1 r V4 M! i/ b& r' }" c' WModifying the model, 模型的修正, _: N* l* L) G) O1 V$ w8 d; |9 o
Modulus of continuity, 连续性模
2 v# J4 X& ~5 P' kMorbidity, 发病率
) R8 F$ g- N# N: C" A$ I) M: iMost favorable configuration, 最有利构形
( Y# E& J2 i- dMultidimensional Scaling (ASCAL), 多维尺度/多维标度; R$ y+ e" f+ n9 V: o4 R3 ^# T
Multinomial Logistic Regression , 多项逻辑斯蒂回归
. e/ P0 y, [" Y- R& T* n( ]/ G6 XMultiple comparison, 多重比较
2 C5 f' @) K$ y S5 h' dMultiple correlation , 复相关3 i9 [9 R+ u% a
Multiple covariance, 多元协方差) I9 u3 w; [9 Z$ J0 w
Multiple linear regression, 多元线性回归
0 I9 N8 _# [& l/ MMultiple response , 多重选项
" H5 h3 c- j! A2 A5 l" t1 ^6 RMultiple solutions, 多解- l4 @4 V, J p0 w
Multiplication theorem, 乘法定理
" ~0 D- ^& D% cMultiresponse, 多元响应( H3 D% j+ O. `
Multi-stage sampling, 多阶段抽样
* f( [5 |8 M/ z1 f6 bMultivariate T distribution, 多元T分布
2 {9 X1 v$ R0 {& k8 MMutual exclusive, 互不相容+ o _; R) [, _% H9 z
Mutual independence, 互相独立8 F; p0 }9 y3 W' J3 `4 Z' J
Natural boundary, 自然边界
/ y) C( O' }6 h, n6 `Natural dead, 自然死亡
5 k K; v7 o- r8 u+ PNatural zero, 自然零
* E' s6 a" e1 Q+ ~Negative correlation, 负相关# a1 _$ v* m" Z
Negative linear correlation, 负线性相关
' N- T0 M7 l: U$ g$ TNegatively skewed, 负偏
}* Q. B: o# M$ n; ^/ mNewman-Keuls method, q检验% R# O. _; r- f: {! r8 o8 ~: R
NK method, q检验0 i+ r1 ^, S- N! C
No statistical significance, 无统计意义! t5 i$ @1 @3 o; |
Nominal variable, 名义变量# p3 c# m* o8 ^& B$ s
Nonconstancy of variability, 变异的非定常性
. F2 j; m+ }0 ~$ a: tNonlinear regression, 非线性相关9 X: _! |7 G$ t1 C) |2 r+ V4 x
Nonparametric statistics, 非参数统计
' A6 S3 ~% J. ?Nonparametric test, 非参数检验* p) w( K$ V+ e @0 ?: S- f% C
Nonparametric tests, 非参数检验* P. O) [4 A a; A
Normal deviate, 正态离差) ^+ }. E# h! N8 [ O" T
Normal distribution, 正态分布# c! O2 B) h3 X8 X8 D/ o
Normal equation, 正规方程组
H2 a- W5 z0 A* ENormal ranges, 正常范围% } a a2 c* T8 |. D# N
Normal value, 正常值
# |6 R9 Q1 U! p% y9 H4 s+ z( G6 B: D3 lNuisance parameter, 多余参数/讨厌参数
4 l4 k1 ]7 U+ { LNull hypothesis, 无效假设
3 Z9 ~6 h Q# ~9 u7 `4 ]Numerical variable, 数值变量
+ G% t; e/ D' c% A3 P* AObjective function, 目标函数+ Q r& V; W& z0 }
Observation unit, 观察单位
2 K. _" s9 k# a1 oObserved value, 观察值5 v& I0 f% X' @. q& W
One sided test, 单侧检验
% h( E& R9 p% g" z+ `One-way analysis of variance, 单因素方差分析& N. S) B, s- F
Oneway ANOVA , 单因素方差分析" j% t0 O, K& I+ |6 `) b; z
Open sequential trial, 开放型序贯设计) Y2 }9 O1 i& C/ e' Q! w
Optrim, 优切尾
}5 {+ \- S6 v: ?9 K7 ROptrim efficiency, 优切尾效率9 g5 k0 @1 X$ R! s% j; @% { \
Order statistics, 顺序统计量
7 E6 _2 [/ l X" ?7 {Ordered categories, 有序分类
# h& G. a5 _( I: B$ R# X7 v) F* pOrdinal logistic regression , 序数逻辑斯蒂回归1 g% E! d' a: D0 R. K
Ordinal variable, 有序变量
, u; ^ W6 z7 Y/ U! vOrthogonal basis, 正交基
2 d! K& O8 y6 u$ h' A8 LOrthogonal design, 正交试验设计
0 \7 E9 N+ C" g* t0 H5 K* T1 cOrthogonality conditions, 正交条件' U" M4 o+ y& u
ORTHOPLAN, 正交设计 6 H4 E, g. }7 A9 s; U% f) W8 X
Outlier cutoffs, 离群值截断点
0 M& a2 b7 f" D) l! h; T8 p% N& tOutliers, 极端值- Z$ M" D- `3 I5 e, M+ ?5 r# z
OVERALS , 多组变量的非线性正规相关 $ R k/ R. ^/ | T2 T5 g
Overshoot, 迭代过度& o2 g7 x# h* J4 j2 B& x; P& n
Paired design, 配对设计9 o6 I" J1 V: E! ~7 k/ W8 y* \& j
Paired sample, 配对样本6 U9 @1 v& T% i( [& a m, q
Pairwise slopes, 成对斜率
7 h G+ z- c; ]5 w7 lParabola, 抛物线0 E5 C, V9 d2 e$ ?& P% w
Parallel tests, 平行试验# g6 p$ c6 X6 V
Parameter, 参数
2 j8 o: p R7 I, k5 Y. RParametric statistics, 参数统计
2 R4 Y9 v$ w/ U/ a9 _4 y2 n: ZParametric test, 参数检验
- e, P4 {5 N! d5 B1 TPartial correlation, 偏相关
, m# Z- P2 Y9 ~) rPartial regression, 偏回归 y. S( ~( H5 C
Partial sorting, 偏排序
" T" [# d8 X" `& Z4 z x9 F8 ZPartials residuals, 偏残差
8 N! f! b+ M9 r! nPattern, 模式
6 m8 X! G+ A. ]- o- y( Q8 PPearson curves, 皮尔逊曲线) s: z) Y3 D3 }: g0 G+ A
Peeling, 退层6 w. J7 F% I# p
Percent bar graph, 百分条形图
$ e! T5 ~% E; [9 [" H. K$ c7 rPercentage, 百分比
% p) m% ]) e6 ~, L" j. o+ A( {Percentile, 百分位数& b* h7 [7 j( `. B& U
Percentile curves, 百分位曲线" q7 |. b" c& \( r. Y+ d/ n
Periodicity, 周期性
5 \' Y$ b/ S' ~% j3 v% oPermutation, 排列9 t; w; g6 r" E3 N: ]
P-estimator, P估计量
0 T' ~, P/ |. ^7 X9 [: l8 fPie graph, 饼图2 d. A' X) G6 b f* a1 G4 K
Pitman estimator, 皮特曼估计量
7 M! |6 H" M$ x/ c/ L8 x, PPivot, 枢轴量
& K. `5 [+ J: @, I% J' YPlanar, 平坦/ h) v8 n1 \( M7 ^5 N& p, A e
Planar assumption, 平面的假设
6 R% H8 O3 x; UPLANCARDS, 生成试验的计划卡
) r; M F3 I5 \" t* d8 E; qPoint estimation, 点估计: S* Z' L) {0 W6 U: J0 h: G
Poisson distribution, 泊松分布* m+ j1 }' c% d: {( P
Polishing, 平滑
$ }/ C$ w4 h; SPolled standard deviation, 合并标准差+ v3 h2 V- }3 k/ A y
Polled variance, 合并方差
. q, V! a. l# _0 a! l8 S$ u. G) H% zPolygon, 多边图& ~1 _% W8 J N- t
Polynomial, 多项式
3 f) Q$ t8 J3 TPolynomial curve, 多项式曲线; J! @8 K- ~% k3 r
Population, 总体' N9 f6 A f' u- ^/ N+ T9 ~
Population attributable risk, 人群归因危险度1 ]8 E# `$ `# z; b$ L/ L
Positive correlation, 正相关
9 q' [( ]- H8 Z. ]Positively skewed, 正偏0 g0 L1 |* Y, n5 l, a% O
Posterior distribution, 后验分布9 J1 ]/ j- _2 P, N* w- I8 ~4 b
Power of a test, 检验效能
1 d3 f! k2 Q9 Q4 Z5 k, v* Q, APrecision, 精密度
* O/ F* {/ k. Y* c- {) m7 L6 ZPredicted value, 预测值
, v' Q& J( U! h9 C6 E; ~, o! VPreliminary analysis, 预备性分析
: R3 e; x B- [( YPrincipal component analysis, 主成分分析* W% l" Y/ ^4 r9 e L
Prior distribution, 先验分布
( b' I9 w5 m/ ~, j, z. E5 N" fPrior probability, 先验概率
" y: H- S" v. y" X5 yProbabilistic model, 概率模型- E7 e3 g* N) A9 r% p
probability, 概率8 A" O x- z+ c4 [! S' Z% {( V& P
Probability density, 概率密度$ z8 Y: C1 n" ?0 }% G' n& E4 `
Product moment, 乘积矩/协方差
3 i @: P, {9 ~( M e, b/ C- G0 uProfile trace, 截面迹图
1 r6 u# X4 z/ @/ x7 N/ u: U) F$ [Proportion, 比/构成比
* h% t% ]5 G* kProportion allocation in stratified random sampling, 按比例分层随机抽样: E5 ~2 P" M# i( ]6 t
Proportionate, 成比例
$ X" r* W+ ^; v0 j$ i, `Proportionate sub-class numbers, 成比例次级组含量+ Y' m8 P- a7 ]5 @. j6 G0 ^' U
Prospective study, 前瞻性调查+ J0 S9 C7 t `6 ]; J8 q
Proximities, 亲近性
+ h+ u; f0 p9 y1 A% ePseudo F test, 近似F检验
7 n* x9 S1 d; `7 i F7 }) UPseudo model, 近似模型$ V+ O# v- k C' ^' s9 c5 F0 a$ S
Pseudosigma, 伪标准差
% E7 f9 _" ^$ @( l+ ]. aPurposive sampling, 有目的抽样& U+ f, R. k1 j3 |- l) K3 g
QR decomposition, QR分解- u+ M, Q# X A9 \$ U% h+ P
Quadratic approximation, 二次近似
6 P7 C% p. ` M# L: V/ @Qualitative classification, 属性分类1 h1 Z( N( W$ `5 }
Qualitative method, 定性方法# e1 X% |% H( s% d
Quantile-quantile plot, 分位数-分位数图/Q-Q图& W; k! q/ A) ] G. V
Quantitative analysis, 定量分析3 g9 j" i' Y/ w& P( F
Quartile, 四分位数
# G, c# v2 O) X( z: o5 V4 TQuick Cluster, 快速聚类
! c4 b- D8 u. b R4 u9 j6 P: pRadix sort, 基数排序6 ?* o% g/ h( }( v
Random allocation, 随机化分组
7 \; L" z/ l R* d! d/ L5 ? g! m9 s2 XRandom blocks design, 随机区组设计
1 D) d2 L: |2 V g1 LRandom event, 随机事件
5 h! y; e6 C4 `* x, ]; KRandomization, 随机化1 w( h) U5 P7 S6 `# w
Range, 极差/全距( Z: p; v, M, e' T( e Q
Rank correlation, 等级相关' n- u: h6 g* o+ V
Rank sum test, 秩和检验; F4 I& D- D( b" T* A* m
Rank test, 秩检验& P# Y% j, A* F& M; d
Ranked data, 等级资料
3 h; P. c" q/ `2 R4 ]4 }2 kRate, 比率
/ ?; N+ x8 [4 Q- ~ yRatio, 比例 t o; v- {7 g5 a, i/ y
Raw data, 原始资料- t0 O* `! M+ N) g3 {+ Z4 U
Raw residual, 原始残差
' z; h U1 k. s6 j# I" ARayleigh's test, 雷氏检验
8 q6 `: k* F/ VRayleigh's Z, 雷氏Z值 " t" b2 [0 K" _) A
Reciprocal, 倒数, m; K2 g' j' [
Reciprocal transformation, 倒数变换, q- k6 {# R0 C4 i% Z
Recording, 记录) L5 C4 [1 M6 L6 `1 Z
Redescending estimators, 回降估计量
: ^ P2 J A$ `. b2 B' S2 Y) yReducing dimensions, 降维
J; D/ x% C+ M, n* R3 m6 I3 D/ X; @Re-expression, 重新表达( b% U: e! K+ M
Reference set, 标准组; V! d( t ^7 |5 `" _
Region of acceptance, 接受域 R4 p4 B4 r/ ^ ?7 L
Regression coefficient, 回归系数) @- L* q2 q: n! h; g+ b: W; F" _
Regression sum of square, 回归平方和
! ]& D! j, z& Q2 N: W W! w7 nRejection point, 拒绝点. }* N' G3 N9 h! g n+ B
Relative dispersion, 相对离散度
) _+ @2 T: u* j# ^; r/ w/ h5 S3 NRelative number, 相对数( h; W: x' s7 Q4 B9 j
Reliability, 可靠性) r0 D$ M; Y" M) M
Reparametrization, 重新设置参数
: ~& o1 C4 f: ]$ h4 _Replication, 重复
+ v1 o+ c! f, J+ b, K" \4 qReport Summaries, 报告摘要
8 {6 v4 O6 k* Q1 f; n, R OResidual sum of square, 剩余平方和# d9 r. I! F- t8 Q
Resistance, 耐抗性
7 I' r7 X: F2 @) h; X2 BResistant line, 耐抗线9 `5 I/ E* [$ Q" L* N! |
Resistant technique, 耐抗技术1 J( B" U4 y/ O( @( d" n, H: n1 Y
R-estimator of location, 位置R估计量
8 h0 ~3 v8 W, B9 d+ ]R-estimator of scale, 尺度R估计量
2 B: V& [% u2 z" G% m2 @Retrospective study, 回顾性调查8 \7 Q! X, ]. t; w$ M
Ridge trace, 岭迹+ y# \$ J2 Y2 j& \! b: r
Ridit analysis, Ridit分析
# P2 V" j- v( d$ _9 U0 oRotation, 旋转1 D9 ~- d4 g0 ^8 p, A! o" X- o- Z5 U
Rounding, 舍入
- b. \ f2 ^. t0 `. ]1 |, b4 V, HRow, 行1 g3 c3 W2 c" b5 f$ k
Row effects, 行效应0 C6 }6 c& b5 \
Row factor, 行因素
; u6 [) T1 H! e4 E# L1 M, VRXC table, RXC表 |9 z& ~6 |3 u; G: Z9 i+ W
Sample, 样本4 G! @: p( d' W. h0 ?, l
Sample regression coefficient, 样本回归系数
5 M' r* l; t$ WSample size, 样本量
^' U( j( ~1 A* n+ _: z1 t) ZSample standard deviation, 样本标准差
9 ^$ R' O* ]( Q" jSampling error, 抽样误差3 v" J( L' u5 [0 V6 D
SAS(Statistical analysis system ), SAS统计软件包2 D$ F0 V0 S6 q, c# Z; B
Scale, 尺度/量表
4 M& v7 Y9 A1 O hScatter diagram, 散点图
+ s6 M5 j7 D* Z- T2 JSchematic plot, 示意图/简图
; f& X4 u1 C$ d. EScore test, 计分检验
) h. h. W c( @0 k% kScreening, 筛检
2 b; Z" b$ |- R9 f# j) r4 h! o. X. pSEASON, 季节分析 1 J: t1 _# ?9 ^% ~$ b) V s* \
Second derivative, 二阶导数9 ~# y/ i6 d& J" l0 i
Second principal component, 第二主成分# g' w3 {' U/ n& f% X
SEM (Structural equation modeling), 结构化方程模型 Y! N Q5 F& F; ^% S0 l
Semi-logarithmic graph, 半对数图
6 V$ H7 h! A c, q) R4 Z. }Semi-logarithmic paper, 半对数格纸3 C/ V3 Z8 y& w9 m
Sensitivity curve, 敏感度曲线
1 c; ~) B# v' f, z9 WSequential analysis, 贯序分析* N3 P7 k- u" B0 x @* }9 [* a
Sequential data set, 顺序数据集& z H6 k- e4 x. K6 i# I6 X5 a
Sequential design, 贯序设计6 m# M% k. s4 I4 s4 ?6 R+ p" ]6 ?
Sequential method, 贯序法- l' M# p. c+ n3 ?0 V2 Z; Z' O
Sequential test, 贯序检验法) ~$ e. o- Y" n. ]0 W9 E$ Y
Serial tests, 系列试验0 W% o# V: O$ |: T
Short-cut method, 简捷法
4 W2 V+ X7 E( G+ m6 vSigmoid curve, S形曲线
/ d; J- {2 s- |2 ~$ B( uSign function, 正负号函数
; o+ f# c8 S! G/ T( ?' tSign test, 符号检验
0 ]% @) [; _5 b5 ~0 ?# eSigned rank, 符号秩7 H I, x, |+ Y2 D. i, T9 d6 a
Significance test, 显著性检验
1 h5 \& C& T3 b+ YSignificant figure, 有效数字 m# J0 j0 W8 v4 L* W' J
Simple cluster sampling, 简单整群抽样& i( z2 c% b) R5 m! s
Simple correlation, 简单相关% f$ Z# A% ?0 I. S M
Simple random sampling, 简单随机抽样# `4 {5 c0 Z+ G4 S |: o
Simple regression, 简单回归
; L8 }+ D/ m% bsimple table, 简单表
8 O. G5 g' G6 k* l4 S4 r/ c2 dSine estimator, 正弦估计量6 m. i: h& {2 M1 `2 Q& W
Single-valued estimate, 单值估计' e, D p, G; @3 e x; s
Singular matrix, 奇异矩阵
+ {& k8 G/ j( s$ ~ |4 \Skewed distribution, 偏斜分布
4 l8 x2 Z6 }" C6 i$ Z I* MSkewness, 偏度
6 E# r6 p% A D3 eSlash distribution, 斜线分布) A8 V6 A5 Z, ]4 L2 o
Slope, 斜率
0 Z9 ?3 W% `4 n' ~3 HSmirnov test, 斯米尔诺夫检验
+ @. K7 N+ p7 U) J. R0 { ISource of variation, 变异来源* c" {" t. h1 u4 N/ w5 H
Spearman rank correlation, 斯皮尔曼等级相关0 [* o0 o; |* |) z/ L
Specific factor, 特殊因子8 _: H! J/ b. h3 r, I; }
Specific factor variance, 特殊因子方差
: y- j% U( r% i% C5 RSpectra , 频谱4 h, Q7 z# k k
Spherical distribution, 球型正态分布
$ w/ o8 c% r( Y' X+ g" \Spread, 展布 o0 W# ?) Z$ l' E
SPSS(Statistical package for the social science), SPSS统计软件包9 V% H) N9 n1 z% }" { {
Spurious correlation, 假性相关
$ s8 F* u, [. z. y+ ]' {, {$ \Square root transformation, 平方根变换; |% k0 S7 Z: G: z
Stabilizing variance, 稳定方差
- D3 V8 i: \) j0 `$ E( z) [Standard deviation, 标准差4 j/ K) X$ y" G1 u: X8 E
Standard error, 标准误
& V, c2 \) d& y7 f {) e' D+ [Standard error of difference, 差别的标准误
, P2 b1 c, ]/ G5 s2 TStandard error of estimate, 标准估计误差% I( |* F! q6 F, ~7 h+ F- M6 X/ i
Standard error of rate, 率的标准误
r$ c3 `4 x' ^) P- xStandard normal distribution, 标准正态分布
/ e3 j* x' T. G' `9 p4 vStandardization, 标准化9 S% g3 ]$ G' V3 K
Starting value, 起始值
' q9 W6 w! c# T. c. NStatistic, 统计量* I. | D9 X+ G$ D; i5 [
Statistical control, 统计控制
6 S" J, g j. W- p+ q3 oStatistical graph, 统计图
* A: Y6 c" g- a# I) zStatistical inference, 统计推断
+ {' H* N# K! A' O# E0 D2 r0 IStatistical table, 统计表. T9 ^# }8 Q$ }' Y- y2 ]5 z1 M! x
Steepest descent, 最速下降法
) x2 C1 K; E4 X9 p uStem and leaf display, 茎叶图
r. p2 O" g; `5 t+ c* h6 u4 @! t$ KStep factor, 步长因子
. k/ ` C8 K' @* XStepwise regression, 逐步回归% F. N0 v0 L0 m* }! D
Storage, 存8 W9 N6 z$ u4 g$ K
Strata, 层（复数）4 d5 p: {3 y: S/ y* a8 K+ Q1 ]
Stratified sampling, 分层抽样. T, l- M2 z- m* r
Stratified sampling, 分层抽样
: W/ g( v( ~+ O* w6 |. CStrength, 强度
1 W. i$ l% E2 i$ }, LStringency, 严密性% w( U7 ? E3 U9 v& k3 d& v
Structural relationship, 结构关系
6 D) A& o7 ]9 F. fStudentized residual, 学生化残差/t化残差. \8 E$ {& d( n. j
Sub-class numbers, 次级组含量 m5 d; X1 m; |
Subdividing, 分割+ L4 b3 B: e: y E
Sufficient statistic, 充分统计量
9 O6 J4 t# r$ U2 p: GSum of products, 积和* t* y! k" n2 t' d6 O( {( Q8 L
Sum of squares, 离差平方和
: f% l9 z* |8 Z3 Q$ qSum of squares about regression, 回归平方和
, r( v6 c9 H1 d* V2 G0 n! {- sSum of squares between groups, 组间平方和0 M( h, x* F' E& y r6 N1 w( H
Sum of squares of partial regression, 偏回归平方和. ~* t0 h: e5 X, {9 p- U- ~
Sure event, 必然事件0 l- Q! w( A! i7 C$ @7 w/ A
Survey, 调查
/ S+ c; B' H; rSurvival, 生存分析" M8 J; \7 ~! t9 I* S6 E
Survival rate, 生存率: b# P" e' \/ y1 X
Suspended root gram, 悬吊根图
- U" I- B! ~% [2 D5 wSymmetry, 对称
: Y+ R( z0 I/ A. q/ d; w) lSystematic error, 系统误差9 @* Y7 o/ ?7 N* H8 O
Systematic sampling, 系统抽样
% x. U1 I1 `9 RTags, 标签& K w: s/ v3 W3 o% t+ n4 r% U! M
Tail area, 尾部面积 w" d! J* J( u& b
Tail length, 尾长
1 H. L1 g- \- d. n4 gTail weight, 尾重
7 m$ ^! _2 l2 ]Tangent line, 切线
% ?$ N7 e) t/ K+ u- v, eTarget distribution, 目标分布9 o) z1 J* J; J
Taylor series, 泰勒级数* V4 C/ P% r" x# ]& y, K
Tendency of dispersion, 离散趋势
6 W+ ~3 g# A' y4 w# |! L8 f0 XTesting of hypotheses, 假设检验
: u% Q; j0 s" A0 c2 YTheoretical frequency, 理论频数7 T& M# E" L5 W/ Y& f1 I0 e
Time series, 时间序列
" o, |- W( Y7 A0 hTolerance interval, 容忍区间
8 x, j1 I% ?8 M G+ E; CTolerance lower limit, 容忍下限! X% `: k- Q+ Q7 h: z, e
Tolerance upper limit, 容忍上限
( w2 n) \0 L: t6 m7 ~7 LTorsion, 扰率" S: \7 X) S: b, A2 |
Total sum of square, 总平方和1 M. m4 i3 _! n% D! t( R
Total variation, 总变异! g O# T$ s4 w. n P. |
Transformation, 转换
) i+ S& `7 x0 Q! `, nTreatment, 处理# b: s$ ?; Y L4 y+ _- o3 r+ B
Trend, 趋势
8 E' q3 w K9 G; a: L6 wTrend of percentage, 百分比趋势
6 |5 }! G3 C4 S- q. S) R/ aTrial, 试验5 Y" e! B# ]- d4 H; y+ M/ g$ @; Y
Trial and error method, 试错法5 ]0 B; e0 E3 @" K5 X
Tuning constant, 细调常数5 J1 T- l2 V8 Y _
Two sided test, 双向检验# t0 E1 P% a3 t# p- U. d
Two-stage least squares, 二阶最小平方
8 S/ V" i( O# qTwo-stage sampling, 二阶段抽样
. F6 b K' G1 }) W7 ^ B4 DTwo-tailed test, 双侧检验
8 X& x! h; g7 O/ W9 M. D. E7 oTwo-way analysis of variance, 双因素方差分析
* t: w" t' w1 O8 c( xTwo-way table, 双向表- R* s, s- H/ T$ }1 j8 y' o
Type I error, 一类错误/α错误
( ^" e6 F3 Q0 i- P* o/ j L- uType II error, 二类错误/β错误( \9 q' a; ~4 ~) y3 ?( ~& F
UMVU, 方差一致最小无偏估计简称
5 Q% A) }, {. Z2 W1 ?Unbiased estimate, 无偏估计" x0 l/ I4 A4 s) i- i
Unconstrained nonlinear regression , 无约束非线性回归
! m# ]. ^* V7 \( j/ [Unequal subclass number, 不等次级组含量
6 f- e* `7 D- h. S% \Ungrouped data, 不分组资料% L. k- `/ g) W* n, m
Uniform coordinate, 均匀坐标
A# W' ^7 O+ [( v9 S6 {Uniform distribution, 均匀分布
" x# K4 Q/ v8 s/ X; F' f, }Uniformly minimum variance unbiased estimate, 方差一致最小无偏估计' A# T% A/ G x& }( \% f% \. _
Unit, 单元
- h W, n# F$ {Unordered categories, 无序分类6 L! S! W% l9 c' |5 {
Upper limit, 上限1 G8 ~% l9 e' b) ^2 {1 X! o8 L
Upward rank, 升秩
: x1 N+ S; W& sVague concept, 模糊概念( m- Y5 Q2 W) B, G: i- }: d
Validity, 有效性! h2 v9 v/ m4 B& m- U
VARCOMP (Variance component estimation), 方差元素估计
@) L4 q% [6 xVariability, 变异性
. _# s8 ]. j$ ^( JVariable, 变量
$ ^ d- l9 _* X+ W& t6 f Z3 s8 bVariance, 方差& }' k0 p1 p1 s( p
Variation, 变异/ f) n: k% G" u- s" }, @5 M
Varimax orthogonal rotation, 方差最大正交旋转3 V: _. E. B2 `* h" K% }- G5 Z
Volume of distribution, 容积
9 {% p" N }8 p# e/ `W test, W检验
$ ^4 U; V; n- }. |) ~Weibull distribution, 威布尔分布
& f( T" y1 G% |Weight, 权数) o6 L' m- w- X1 e
Weighted Chi-square test, 加权卡方检验/Cochran检验
4 M/ @1 X# I- U H1 y3 ~( MWeighted linear regression method, 加权直线回归8 ?, q; R: p4 N& @4 |
Weighted mean, 加权平均数4 q t/ n& V2 h# @( {8 D5 o6 f
Weighted mean square, 加权平均方差
! R9 N$ K! [2 H7 y$ O+ JWeighted sum of square, 加权平方和
* \- {6 S8 D$ W) B( j0 KWeighting coefficient, 权重系数' G+ H0 q( [) `: c; |
Weighting method, 加权法
4 ~0 ?2 D$ t9 Z9 RW-estimation, W估计量
* H3 o9 n, b( ]3 Z+ n" q, o; gW-estimation of location, 位置W估计量- p6 g8 p) n& C3 d% h$ x, x
Width, 宽度
# S0 [3 o' _3 d1 p3 ^" fWilcoxon paired test, 威斯康星配对法/配对符号秩和检验
: K ?' F( a, q3 w9 ?Wild point, 野点/狂点! b- |7 }. }+ T% m% g6 C9 O1 q+ ]
Wild value, 野值/狂值
) x G6 q: l0 Z% v- G7 y8 Z' UWinsorized mean, 缩尾均值
4 }5 x' K: i. S2 Z% H. m7 ZWithdraw, 失访
% X8 `7 Q k! cYouden's index, 尤登指数& p7 ?5 ~+ x' J8 e* u
Z test, Z检验
/ t( h9 e/ T0 h3 s% MZero correlation, 零相关 Y$ l, i, O; `2 x: ?0 o
Z-transformation, Z变换 |
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发表于 2009-1-6 22:05
